Abstract-Jamming attackers can dramatically increase attack efficiency and stealth by randomly or periodically cycling the jamming transmission on and off, attacks respectively known as random and periodic jamming. In this paper, we analyze the impact of such attacks on the IEEE 802.15.4 communication protocol, commonly used in wireless sensor networking applications, and show that the cycling behavior introduces a narrow spectral component into the received signal. We propose the inclusion of a digital filter at the receiver side to effectively eliminate this spectral component, and we discuss the benefits involved in this filter design. We evaluate the impacts of random and periodic jamming with and without the proposed filter, through implementation in software defined radios. Through our evaluation, we observe over 90% reduction in packet error rate with the proposed digital filter.

Traffic is not only a source of frustration but also a leading cause of death for people under 35 years of age. Recent research has focused on how driver assistance technologies can be used to mitigate traffic fatalities and create more enjoyable commutes. In this work, we consider cooperative adaptive cruise control (CACC) or platooning, a driver assistance technology that controls the speed of vehicles and inter-vehicle spacing. CACC equipped cars use radar to fine tune inter-vehicle spacing and dedicated short-range communication (DSRC) to collaboratively accelerate and decelerate. Platooning can reduce fuel consumption by over 5% and increases the density of cars on a highway. Previous work on platooning has focused on proving string stability, which guarantees that the error between cars does not grow with the length of a platoon, but little work has considered the impact an attacker can have on a platoon. To design safe distributed controllers and networks it is essential to understand the possible attacks that could be mounted against platoons.In this work, we design a set of insider attacks and abnormal behaviors that occur in a platoon of cars. For example, we introduce the collision induction attack where an attacker exploits the platoon controller to cause a high-speed accident with the car following it. To mitigate these insider attacks we design a model-based detection scheme that leverages the broadcast nature of DSRC. Each car uses DSRC messages from other cars in the platoon to model the expected behavior of the car directly preceding it. If the expected behavior and actual behavior differ the monitoring vehicle switches to non-cooperative ACC, relying solely on radar, to mitigate the impact of the attack. We show that our detection scheme is able to detect many of our proposed insider attacks and when combined with a well designed ACC controller can avoid collisions. We propose combining our detection scheme with a global reputation scheme to detect when a car is malicious or needs maintenance.

The Internet of Things (IoT) paradigm comprises a heterogenous mix of connected devices connected to the Internet. This promises a a wealth of opportunity for a large collection of distributed applications and services. However, the IoT introduces significant changes to the Internet model, largely in the form of billions to trillions of embedded devices that most likely will not be able to be managed centrally by cloud services due to lack of scalability. We suggest that the natural direction for IoT devices is to manage themselves, both in terms of their software/hardware configuration and their resource utilization. In this work, we descibe the underlying framework for selfmanaging devices, comprising measurement-based learning and adaptation to changing system context and application demands. In addition, we describe several upcoming research challenges in order to realize this self-management vision.

Abstract-Despite the widespread commercial use of spread spectrum technology, advanced algorithms and modern hardware capabilities still allows efficient denial-of-service attacks against wireless communication systems using jamming. Much of the recent work on jamming mitigation has focused on how to adjust the transmitter-receiver system once a jamming attack has been detected. However, characterizing the detectability of certain classes of jamming attacks remains a largely unstudied problem. We aim to narrow this gap by analyzing the effect of a class of periodic jamming attacks on the attack detection metrics of packet delivery ratio (PDR) and received signal strength (RSS). We show that a well-designed jamming signal can effectively defeat RSS-based detection while causing a significant and often devastating reduction in PDR, demonstrating that RSS-based detection is insufficient. We further evaluate our claims through implementation of a periodic jammer using a wide range of signal parameters against a transmitter-receiver pair communicating using IEEE 802.15.4, demonstrating the validity of our analytical claims.

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